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This paper briefly describes AIF-EL, an OWL2-EL compliant ontology for the Argument Interchange Format. Publisher PDF

Since the OpenLaws portal is envisioned as an open environment for collaboration between legal professionals, recommendation will eventually become a collaborative filtering problem. This paper addresses the cold start problem for such a portal, where initial recommendations will have to be given, while collaborative filtering data is initially too sparse to produce recommendations. We implemented a hybrid recommendation approach, starting with a latent dirichlet allocation topic model, and progressing to collaborative filtering, and critically evaluated it. Main conclusion is that giving recommendations, even bad ones, will influence user selections.

A growing number of Dutch court judgments is openly distributed on Rechtspraak.nl. Currently, many documents are not marked up or marked up only very sparsely, hampering our ability to process these documents automatically. In this paper, we explore the problem of automatic assignment of a section structure to these texts. We experiment with Linear-Chain Conditional Random Fields to label text elements with their roles in the document (text, title or numbering). In this subtask, we report F1 scores of around 0.91 for tagging section titles, and around 1.0 for the other types. Given a list of labels, we experiment with Probabilistic Context-Free Grammars to generate a parse tree which represents the section hierarchy of a document. In this task, we report an F1 score of 0.92.

When reasoning about the facts of a case, we typically use stories to link the known events into coherent wholes. One way to establish coherence is to appeal to past examples, real or fictitious. These examples can be chosen and critiqued using the case-based reasoning (CBR) techniques from the AI and Law literature. In this paper, we apply these techniques to factual stories, assessing a story about the facts using precedents. We thus show how factual and legal reasoning can be combined in a CBR model.

In this paper we extend a formal framework presented in [6] to model reasoning across legal systems. In particular, we propose a logical system that encompasses the various interpretative interactions occurring between legal systems in the context of private international law. This is done by introducing meta-rules to reason with interpretive canons.

TropICAL is a Domain Specific Language (DSL) for the description of abstract legal policies. Taking inspiration from narrative tropes, our DSL enables the creation of component “policies” that may be reused between case descriptions. These components are compiled to social institutions, which are realised in Answer Set Programming (ASP) code. In this way, the actions of defendant and plaintiff take the shape of a story which must conform to the rules in the ASP description. We propose the use of our DSL in a tool designed for lawyers to generate arguments for the argumentation process.